Inverse transformation using pruning for video coding

ABSTRACT

A method for inverse discrete cosine transformation (IDCT) in video coding is provided that includes receiving a transform block, identifying a region of non-zero transform coefficients in the transform block using a group significance map corresponding to the transform block, wherein any transform coefficients not in the region have a value of zero, applying a one-dimensional (1D) IDCT to the region of non-zero transform coefficients in a first direction to generate an interim results block, wherein 1D IDCT computations are not performed on transform coefficients outside the region, and applying a 1D IDCT to the interim results block in a second direction to generate a residual block.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation U.S. patent application Ser. No.13/917,540 filed Jun. 13, 2013, which claims the benefit of U.S.Provisional Patent Application Ser. No. 61/659,055, filed Jun. 13, 2012,all of which are incorporated herein by reference in their entirety.This application may be related to United States Patent ApplicationSerial No. 2013/470,352, now U.S. Pat. No. 9,747,255 issued Aug. 29,2017, which is incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION Field of the Invention

Embodiments of the present invention generally relate to inversetransformation using pruning in video coding.

Description of the Related Art

Video compression, i.e., video coding, is an essential enabler fordigital video products as it enables the storage and transmission ofdigital video. In general, video compression techniques applyprediction, transformation, quantization, and entropy coding tosequential blocks of pixels in a video sequence to compress, i.e.,encode, the video sequence. Video decompression techniques generallyperform the inverse of these operations in reverse order to decompress,i.e., decode, a compressed video sequence.

Two dimensional (2D) block transforms, e.g., 2D discrete cosinetransforms (DCT), and variants are used in video coding to reducespatial redundancy and achieve compression. Accordingly, 2D inversetransforms, e.g., 2D inverse DCT (IDCT) are performed in video decodingas part of decompressing encoded video. A 2D IDCT is a separabletransform that may be split into row and column one-dimensional (1D)IDCTs for application. The video coding standard in use typicallydefines the order in which the row and column IDCTs are applied so thatan encoded video bit stream is decoded identically in all compliantdecoders. For example, in the H.264/AVC video coding standard, the rowinverse transform is applied first followed by the column inversetransform.

The high frequency region in transform blocks is typically zero due toquantization and the energy compaction properties of the transform. Theknowledge that a large portion of a transform block may be zero isexploited for IDCT pruning, also referred to as partial inversetransformation, to reduce the computational complexity of an IDCT. InIDCT pruning, many 2D IDCT computations that have zero input and zerooutput, i.e., computations corresponding to a region having only zerovalues, may be eliminated to reduce computational complexity. IDCTpruning is a well known technique that is supported by existing videocoding standards that use a zigzag scan pattern to scan coefficients ina transform block.

SUMMARY

Embodiments of the present invention relate to methods and apparatus forinverse transformation using pruning in video coding. In one aspect, amethod for inverse discrete cosine transformation (IDCT) in video codingis provided that includes receiving a transform block, identifying aregion of non-zero transform coefficients in the transform block using agroup significance map corresponding to the transform block, wherein anytransform coefficients not in the region have a value of zero, applyinga one-dimensional (1D) IDCT to the region of non-zero transformcoefficients in a first direction to generate an interim results block,wherein 1D IDCT computations are not performed on transform coefficientsoutside the region, and applying a 1D IDCT to the interim results blockin a second direction to generate a residual block, wherein the firstdirection and the second direction are opposite directions selected froma group consisting of a vertical direction and a horizontal direction.

In one aspect, an apparatus configured to perform inverse discretecosine transformation (IDCT) in video coding is provided that includesmeans for receiving a transform block, means for identifying a region ofnon-zero transform coefficients in the transform block using a groupsignificance map corresponding to the transform block, wherein anytransform coefficients not in the region have a value of zero, means forapplying a one-dimensional (1D) IDCT to the region of non-zero transformcoefficients in a first direction to generate an interim results block,wherein 1D IDCT computations are not performed on transform coefficientsoutside the region, and means for applying a 1D IDCT to the interimresults block in a second direction to generate a residual block,wherein the first direction and the second direction are oppositedirections selected from a group consisting of a vertical direction anda horizontal direction.

In one aspect, a non-transitory computer readable medium storingsoftware instructions is provided. The software instructions, whenexecuted by a processor, cause a method for inverse discrete cosinetransformation (IDCT) in video coding to be performed, the methodincluding receiving a transform block, identifying a region of non-zerotransform coefficients in the transform block using a group significancemap corresponding to the transform block, wherein any transformcoefficients not in the region have a value of zero, applying aone-dimensional (1D) IDCT to the region of non-zero transformcoefficients in a first direction to generate an interim results block,wherein 1D IDCT computations are not performed on transform coefficientsoutside the region, and applying a 1D IDCT to the interim results blockin a second direction to generate a residual block, wherein the firstdirection and the second direction are opposite directions selected froma group consisting of a vertical direction and a horizontal direction.

BRIEF DESCRIPTION OF THE DRAWINGS

Particular embodiments will now be described, by way of example only,and with reference to the accompanying drawings:

FIG. 1 is an example of prior art IDCT pruning for a zigzag scanpattern;

FIGS. 2A and 2B are examples of a significance map and a correspondinggroup significance map;

FIG. 3 is a block diagram of a digital system;

FIG. 4 is a block diagram of a video encoder;

FIG. 5 is a block diagram of a video decoder;

FIGS. 6 and 8 are flow diagrams of methods for IDCT pruning;

FIGS. 7 and 9-14 are examples; and

FIG. 15 is a block diagram of an illustrative digital system.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

Specific embodiments of the invention will now be described in detailwith reference to the accompanying figures. Like elements in the variousfigures are denoted by like reference numerals for consistency.

As used herein, the term “picture” may refer to a frame or a field of aframe. A frame is a complete image captured during a known timeinterval. The Joint Collaborative Team on Video Coding (JCT-VC) of ITU-TWP3/16 and ISO/IEC JTC 1/SC 29/WG 11 is currently developing thenext-generation video coding standard referred to as High EfficiencyVideo Coding (HEVC). HEVC is expected to provide around 50% improvementin coding efficiency over the current standard, H.264/AVC, as well aslarger resolutions and higher frame rates. For convenience ofdescription, embodiments of the invention are described herein inreference to HEVC. One of ordinary skill in the art will understand thatembodiments of the invention are not limited to HEVC.

In HEVC, a largest coding unit (LCU) is the base unit used forblock-based coding. A picture is divided into non-overlapping LCUs. Thatis, an LCU plays a similar role in coding as the macroblock ofH.264/AVC, but it may be larger, e.g., 32×32, 64×64, etc. An LCU may bepartitioned into coding units (CU). A CU is a block of pixels within anLCU and the CUs within an LCU may be of different sizes. Thepartitioning is a recursive quadtree partitioning. The quadtree is splitaccording to various criteria until a leaf is reached, which is referredto as the coding node or coding unit. The maximum hierarchical depth ofthe quadtree is determined by the size of the smallest CU (SCU)permitted. The coding node is the root node of two trees, a predictiontree and a transform tree. A prediction tree specifies the position andsize of prediction units (PU) for a coding unit. A transform treespecifies the position and size of transform units (TU) for a codingunit. A transform unit may not be larger than a coding unit and the sizeof a transform unit may be, for example, 4×4, 8×8, 16×16, 32×32, 4×16,16×4, 8×32, and 32×8. The sizes of the transforms units and predictionunits for a CU are determined by the video encoder during predictionbased on minimization of rate/distortion costs.

Various versions of HEVC are described in the following documents, whichare incorporated by reference herein: T. Wiegand, et al., “WD3: WorkingDraft 3 of High-Efficiency Video Coding,” JCTVC-E603, JointCollaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 andISO/IEC JTC1/SC29/WG11, Geneva, CH, Mar. 16-23, 2011 (“WD3”), B. Bross,et al., “WD4: Working Draft 4 of High-Efficiency Video Coding,”JCTVC-F803_d6, Joint Collaborative Team on Video Coding (JCT-VC) ofITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Torino, IT, Jul. 14-22, 2011(“WD4”), B. Bross. et al., “WD5: Working Draft 5 of High-EfficiencyVideo Coding,” JCTVC-G1103_d9, Joint Collaborative Team on Video Coding(JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Geneva, CH, Nov.21-30, 2011 (“WD5”), B. Bross, et al., “High Efficiency Video Coding(HEVC) Text Specification Draft 6,” JCTVC-H1003_dK, Joint CollaborativeTeam on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IECJTC1/SC29/WG1, San Jose, Calif., Feb. 1-10, 2012, (“HEVC Draft 6”), B.Bross, et al., “High Efficiency Video Coding (HEVC) Text SpecificationDraft 7,” JCTVC-I1003_d9, Joint Collaborative Team on Video Coding(JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG1, Geneva, CH, Apr.17-May 7, 2012 (“HEVC Draft 7”), B. Bross, et al., “High EfficiencyVideo Coding (HEVC) Text Specification Draft 8,” JCTVC-J1003_d7, JointCollaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 andISO/IEC JTC1/SC29/WG1, Stockholm, SE, Jul. 11-20, 2012 (“HEVC Draft 8”),B. Bross, et al., “High Efficiency Video Coding (HEVC) TextSpecification Draft 9,” JCTVC-K1003_v13, Joint Collaborative Team onVideo Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG1,Shanghai, CN, Oct. 10-19, 2012 (“HEVC Draft 9”), and B. Bross, et al.,“High Efficiency Video Coding (HEVC) Text Specification Draft 10 (forFDIS & Last Call),” JCTVC-L1003_v34, Joint Collaborative Team on VideoCoding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG1, Geneva, CH,Jan. 14-23, 2013 (“HEVC Draft 10”).

As previously discussed, inverse transformation with pruning is awell-known technique supported by existing video coding standards suchas H.264/AVC. These video coding standards primarily use a zigzag scanpattern to scan coefficients in a transform block and the largesttransform size used is 8×8. Further, the 2D IDCT needed to inverselytransform a block of transform coefficients may be split into row(horizontal) and column (vertical) one-dimensional (1D) IDCTs forapplication. The video coding standard in use typically defines theorder in which the row and column IDCTs are applied in the decoder. Forrow-column order, a 1D IDCT is performed horizontally on the rows of thetransform block, and a 1D IDCT is performed is then performed verticallyon the columns of the resulting block. For column-row order, a 1D IDCTis performed vertically on the columns of the transform block, and a 1DIDCT is performed is then performed horizontally on the rows of theresulting block.

In general, to perform IDCT pruning when a zigzag scan pattern is used,the decoder determines the position of the last non-zero coefficient ina transform block. A non-zero coefficient may also be referred to as asignificant coefficient herein. This position may be communicated to thedecoder in the encoded bit stream being decoded. Given the position onthe last non-zero coefficient, the decoder can determine how many rows(or columns) of the transform block may have at least one non-zerocoefficient. For example, assuming a square transform block, for mostpossible positions of the last non-zero coefficient, the sum of thecoordinates (x,y) of the position relative to the upper left corner(0,0) of the transform block added to 1 is the number of rows (orcolumns) L that may have at least one non-zero coefficient, i.e.,x+y+1=L.

Because the remaining rows (columns) contain only zeroes, there is noneed to perform the first 1D IDCT on those rows (columns) as thecomputation results for those rows (columns) will be zero. Accordingly,for row-column order, the computations of the 1D IDCT are performed onlyon the first L rows of the transform block and the remaining rows of theresulting block are assumed to be zero. Similarly, for column-row order,the computations of the 1D IDCT are performed only on the first Lcolumns of the transform block and the remaining columns of theresulting block are assumed to be zero.

FIG. 1 shows an example of IDCT pruning when a zigzag scan pattern isused for a transform block and row-column order for the IDCT is used.The non-shaded regions of each block indicate the region of the blockcontaining only zero coefficients. In this example, the input transformblock 100 is a 16×16 block. The position of the last non-zerocoefficient in the block, indicated by the X, is (3,3), assuming the topleft coordinate is (0,0). Thus, the number of rows that may have atleast one non-zero coefficient is x+y+1=3+3+1=7. The last 9 rows are allzero. The first seven rows of the transform block 100 are transformedusing the 1D IDCT to generate the first seven rows of the interimresults block 102 as only the first 7 rows of the transform block 100may have non-zero values. The remaining rows in the interim resultsblock 102 are assumed to be 0. Then, all of the columns of the interimresults block 102 are transformed using the 1D IDCT to generate thefinal inversely transformed output block 104.

HEVC includes large size 2D transforms, e.g., 16×16 and 32×32, toachieve improved compression performance. The large transforms have highcomputational complexity so techniques such as pruning are needed toreduce this computational complexity. Basing the amount of pruning onthe quantity m+n+1 as estimated from the position of the last non-zerocoefficient in a transform block provides a loose upper bound on thenumber of rows (columns) in the transform block that may containsignificant coefficient values. For example, in the case of FIG. 1,prior art techniques will assume that the first seven rows may containnon-zero coefficient values. In actuality, only the first four rowsinclude significant coefficient values. For the larger transforms ofHEVC, pruning techniques that may result in a tighter upper bound on thenumber of rows (columns) that may include non-zero coefficient valuesare desirable as even larger regions of such transform blocks may bezero.

In HEVC, as well as in H.264/AVC, the locations of non-zero transformcoefficients in transform blocks are transmitted using significancemaps. A significance map includes 1 bit flag for each coefficientlocation in a transform block. If the flag corresponding to a transformcoefficient location is 1, the coefficient value is non-zero; otherwise,the value is zero. In HEVC, each individual flag in the significance mapis referred to as a significant_coeff_flag. FIG. 2A shows thesignificance map for the example 16×16 transform block of FIG. 1. Thesignificant coefficient flags with the value of 1 in the significancemap indicate the non-zero coefficients A, B, C and X.

To reduce the number of significant coefficient flags that may betransmitted, HEVC uses a multilevel significance map coding scheme fortransform blocks that includes a significance map and a groupsignificance map. More specifically, to generate a group significancemap for a transform block, the significance map of a transform block islogically divided into non-overlapping 4×4 blocks. Each entry in thegroup significance map is a significant coefficient group flag, referredto as a significant_coeff_group_flag, which represents one of theseblocks. If the value of a significant coefficient group flag is 1, thecorresponding 4×4 block of the significance map includes at least onenon-zero significant coefficient flag, thus indicating that thecorresponding transform block includes at least one non-zero transformcoefficient in a corresponding 4×4 block; otherwise, the values of thesignificant coefficient flags in the corresponding block of thesignificance map are all zero. To signal the coefficient information,each significant coefficient group flag is signaled, followed by thesixteen significant coefficient flags of the corresponding 4×4 block, ifthe value of the significant coefficient group flag is 1. If the valueof a significant coefficient group flag is 0, then all of thesignificant coefficient flag values in the corresponding 4×4 block are0. In such a case, no significant coefficient flags are signaled, andthe next significant coefficient group flag is signaled.

For example, FIG. 2A shows the 4×4 blocks of the significance map forthe 16×16 transform block of FIG. 1 and FIG. 2B shows the groupsignificance map for the significance map of FIG. 2A. Note that in thisparticular example, the only non-zero significant coefficient flags inthe significance map of FIG. 2A are in the upper left 4×4 block. Thus,in the group significance map of FIG. 2B, only one significantcoefficient group flag has a value of 1. To signal the coefficientinformation for this example, the value of the significant coefficientgroup flag in the top left corner of the group significance map is firstsignaled. Since the value of this flag is 1, the 16 significantcoefficient flags of the corresponding 4×4 block in the top left cornerof the significance map are signaled following the significantcoefficient group flag. Since the rest of the significant coefficientgroup flags are 0, the values of each of those flags are subsequentlysignaled but no additional significant coefficient flags are signaled.

Embodiments of the invention provide for techniques for IDCT withpruning based on information available from group significance maps.More specifically, the group significance map of a transform block maybe used to determine the number of rows (columns) of the transform blockthat may include non-zero coefficient values for IDCT pruning instead ofusing the position of the last non-zero coefficient as in the prior art.Using the group significance map may result in a tighter bound on thenon-zero region of a transform block than that found using the positionof the last non-zero coefficient. For example, analysis of the groupsignificance map of FIG. 2B shows that only the first four rows of thetransform block may include non-zero coefficient values as only thesignificant coefficient group flag at position (0,0) has a value of 1.In comparison, prior art techniques that use the signaled lastsignificant coefficient position conclude that the first seven rows arenon-zero. Assuming row-column order, fewer rows need to be transformedby the first 1D IDCT than in the prior art, which reduces computationalcomplexity.

In some embodiments, optimized IDCT pruning for predetermined categoriesof rectangular distribution patterns of non-zero coefficients intransform blocks is provided. As is explained in more detail herein, therectangular distribution pattern of non-zero coefficients in a transformblock is determined from information in the corresponding groupsignificance map and then used to determine if the distribution patternfits into one of the predetermined distribution categories, an optimized1D IDCT implementation for the distribution category is used for inversetransformation of the transform block.

FIG. 3 shows a block diagram of a digital system that includes a sourcedigital system 300 that transmits encoded video sequences to adestination digital system 302 via a communication channel 316. Thesource digital system 300 includes a video capture component 304, avideo encoder component 306, and a transmitter component 308. The videocapture component 304 is configured to provide a video sequence to beencoded by the video encoder component 306. The video capture component304 may be, for example, a video camera, a video archive, or a videofeed from a video content provider. In some embodiments, the videocapture component 304 may generate computer graphics as the videosequence, or a combination of live video, archived video, and/orcomputer-generated video.

The video encoder component 306 receives a video sequence from the videocapture component 304 and encodes it for transmission by the transmittercomponent 308. The video encoder component 306 receives the videosequence from the video capture component 304 as a sequence of pictures,divides the pictures into largest coding units (LCUs), and encodes thevideo data in the LCUs. The video encoder component 306 may beconfigured to apply IDCT pruning techniques during the encoding processas described herein. An embodiment of the video encoder component 306 isdescribed in more detail herein in reference to FIG. 4.

The transmitter component 308 transmits the encoded video data to thedestination digital system 302 via the communication channel 316. Thecommunication channel 316 may be any communication medium, orcombination of communication media suitable for transmission of theencoded video sequence, such as, for example, wired or wirelesscommunication media, a local area network, or a wide area network.

The destination digital system 302 includes a receiver component 310, avideo decoder component 312 and a display component 314. The receivercomponent 310 receives the encoded video data from the source digitalsystem 300 via the communication channel 316 and provides the encodedvideo data to the video decoder component 312 for decoding. The videodecoder component 312 reverses the encoding process performed by thevideo encoder component 306 to reconstruct the LCUs of the videosequence. The video decoder component 312 may be configured to applyIDCT pruning techniques during the decoding process as described herein.An embodiment of the video decoder component 312 is described in moredetail below in reference to FIG. 5.

The reconstructed video sequence is displayed on the display component314. The display component 314 may be any suitable display device suchas, for example, a plasma display, a liquid crystal display (LCD), alight emitting diode (LED) display, etc.

In some embodiments, the source digital system 300 may also include areceiver component and a video decoder component and/or the destinationdigital system 302 may include a transmitter component and a videoencoder component for transmission of video sequences both directionsfor video steaming, video broadcasting, and video telephony. Further,the video encoder component 306 and the video decoder component 312 mayperform encoding and decoding in accordance with one or more videocompression standards. The video encoder component 306 and the videodecoder component 312 may be implemented in any suitable combination ofsoftware, firmware, and hardware, such as, for example, one or moredigital signal processors (DSPs), microprocessors, discrete logic,application specific integrated circuits (ASICs), field-programmablegate arrays (FPGAs), etc.

FIG. 4 is a block diagram of the LCU processing portion of an examplevideo encoder. The LCU processing receives LCUs 400 of the input videosequence from a coding control component (not shown) and encodes theLCUs 400 under the control of the coding control component to generatethe compressed video stream. The LCUs 400 in each picture are processedin row order.

The coding control component sequences the various operations of thevideo encoder, i.e., the coding control component runs the main controlloop for video encoding. For example, the coding control component 340performs processing on the input video sequence that is to be done atthe picture level, such as determining the coding type (I, P, or B) of apicture based on a high level coding structure, e.g., IPPP, IBBP,hierarchical-B, and dividing a picture into LCUs for further processing.

In addition, for pipelined architectures in which multiple LCUs may beprocessed concurrently in different components of the LCU processing,the coding control component controls the processing of the LCUs byvarious components of the LCU processing in a pipeline fashion. Forexample, in many embedded systems supporting video processing, there maybe one master processor and one or more slave processing modules, e.g.,hardware accelerators. The master processor operates as the codingcontrol component and runs the main control loop for video encoding, andthe slave processing modules are employed to off load certaincompute-intensive tasks of video encoding such as motion estimation,motion compensation, intra prediction mode estimation, transformationand quantization, entropy coding, and loop filtering. The slaveprocessing modules are controlled in a pipeline fashion by the masterprocessor such that the slave processing modules operate on differentLCUs of a picture at any given time. That is, the slave processingmodules are executed in parallel, each processing its respective LCUwhile data movement from one processor to another is serial.

The LCUs 400 from the coding control component are provided as one inputof a motion estimation component (ME) 420, as one input of anintra-prediction estimation component (IPE) 424, and to a positive inputof a combiner 402 (e.g., adder or subtractor or the like). Further,although not specifically shown, the prediction mode of each picture asselected by the coding control component is provided to a mode decisioncomponent 428 and an entropy coding component 436.

The storage component 418 provides reference data to the motionestimation component 420 and to the motion compensation component 422.The reference data may include one or more previously encoded anddecoded pictures, i.e., reference pictures.

The motion estimation component 420 provides motion data information tothe motion compensation component 422 and the entropy coding component436. More specifically, the motion estimation component 420 performstests on CUs in an LCU based on multiple inter-prediction modes (e.g.,skip mode, merge mode, and normal or direct inter-prediction), PU sizes,and TU sizes using reference picture data from storage 418 to choose thebest CU partitioning, PU/TU partitioning, inter-prediction modes, motionvectors, etc. based on coding cost, e.g., a rate distortion coding cost.To perform the tests, the motion estimation component 420 may divide anLCU into CUs according to the maximum hierarchical depth of thequadtree, and divide each CU into PUs according to the unit sizes of theinter-prediction modes and into TUs according to the transform unitsizes, and calculate the coding costs for each PU size, prediction mode,and transform unit size for each CU. The motion estimation component 420provides the motion vector (MV) or vectors and the prediction mode foreach PU in the selected CU partitioning to the motion compensationcomponent (MC) 422.

The motion compensation component 422 receives the selectedinter-prediction mode and mode-related information from the motionestimation component 420 and generates the inter-predicted CUs. Theinter-predicted CUs are provided to the mode decision component 428along with the selected inter-prediction modes for the inter-predictedPUs and corresponding TU sizes for the selected CU/PU/TU partitioning.The coding costs of the inter-predicted CUs are also provided to themode decision component 428.

The intra-prediction estimation component 424 (IPE) performsintra-prediction estimation in which tests on CUs in an LCU based onmultiple intra-prediction modes, PU sizes, and TU sizes are performedusing reconstructed data from previously encoded neighboring CUs storedin a buffer (not shown) to choose the best CU partitioning, PU/TUpartitioning, and intra-prediction modes based on coding cost, e.g., arate distortion coding cost. To perform the tests, the intra-predictionestimation component 424 may divide an LCU into CUs according to themaximum hierarchical depth of the quadtree, and divide each CU into PUsaccording to the unit sizes of the intra-prediction modes and into TUsaccording to the transform unit sizes, and calculate the coding costsfor each PU size, prediction mode, and transform unit size for each PU.The intra-prediction estimation component 424 provides the selectedintra-prediction modes for the PUs, and the corresponding TU sizes forthe selected CU partitioning to the intra-prediction component (IP) 426.The coding costs of the intra-predicted CUs are also provided to theintra-prediction component 426.

The intra-prediction component 426 (IP) receives intra-predictioninformation, e.g., the selected mode or modes for the PU(s), the PUsize, etc., from the intra-prediction estimation component 424 andgenerates the intra-predicted CUs. The intra-predicted CUs are providedto the mode decision component 428 along with the selectedintra-prediction modes for the intra-predicted PUs and corresponding TUsizes for the selected CU/PU/TU partitioning. The coding costs of theintra-predicted CUs are also provided to the mode decision component428.

The mode decision component 428 selects between intra-prediction of a CUand inter-prediction of a CU based on the intra-prediction coding costof the CU from the intra-prediction component 426, the inter-predictioncoding cost of the CU from the motion compensation component 422, andthe picture prediction mode provided by the coding control component.Based on the decision as to whether a CU is to be intra- or inter-coded,the intra-predicted PUs or inter-predicted PUs are selected. Theselected CU/PU/TU partitioning with corresponding modes and other moderelated prediction data (if any) such as motion vector(s) and referencepicture index (indices), are provided to the entropy coding component436.

The output of the mode decision component 428, i.e., the predicted PUs,is provided to a negative input of the combiner 402 and to the combiner416. The associated transform unit size is also provided to thetransform component (DCT) 404. The combiner 402 subtracts a predicted PUfrom the original PU. Each resulting residual PU is a set of pixeldifference values that quantify differences between pixel values of theoriginal PU and the predicted PU. The residual blocks of all the PUs ofa CU form a residual CU for further processing.

The transform component 404 performs block transforms on the residualCUs to convert the residual pixel values to transform coefficients andprovides the transform coefficients to a quantize component (Q) 406.More specifically, the transform component 404 receives the transformunit sizes for the residual CU and applies transforms of the specifiedsizes to the CU to generate transform coefficients. Further, thequantize component 406 quantizes the transform coefficients based onquantization parameters (QPs) and quantization matrices provided by thecoding control component and the transform sizes and provides thequantized transform coefficients to the entropy coding component 436 forcoding in the bit stream.

The entropy coding component 436 entropy encodes the relevant data,i.e., syntax elements, output by the various encoding components and thecoding control component using context-adaptive binary arithmetic coding(CABAC) to generate the compressed video bit stream. Among the syntaxelements that are encoded are picture parameter sets, slice headers,flags indicating the CU/PU/TU partitioning of an LCU, significance mapsand group significance maps for TUs, the prediction modes for the CUs,and the quantized transform coefficients for the CUs. The entropy codingcomponent 436 also entropy encodes relevant data from the in-loopfilters, such as the SAO parameters.

The LCU processing includes an embedded decoder. As any compliantdecoder is expected to reconstruct an image from a compressed bitstream, the embedded decoder provides the same utility to the videoencoder. Knowledge of the reconstructed input allows the video encoderto transmit the appropriate residual energy to compose subsequentpictures.

The quantized transform coefficients for each CU are provided to aninverse quantize component (IQ) 412, which outputs a reconstructedversion of the transform result from the transform component 404. Thedequantized transform coefficients are provided to the inverse transformcomponent (IDCT) 414, which outputs estimated residual informationrepresenting a reconstructed version of a residual CU. The inversetransform component 414 receives the transform unit size used togenerate the transform coefficients and applies inverse transform(s) ofthe specified size to the transform coefficients to reconstruct theresidual values. The inverse transform component 414 may perform amethod for IDCT pruning using information from group significance mapsas described herein. The reconstructed residual CU is provided to thecombiner 416.

The combiner 416 adds the original predicted CU to the residual CU togenerate a reconstructed CU, which becomes part of reconstructed picturedata. The reconstructed picture data is stored in a buffer (not shown)for use by the intra-prediction estimation component 424.

Various in-loop filters may be applied to the reconstructed picture datato improve the quality of the reference picture data used forencoding/decoding of subsequent pictures. The in-loop filters mayinclude a deblocking filter 430, a sample adaptive offset filter (SAO)432, and an adaptive loop filter (ALF) 434. The in-loop filters 430,432, 434 are applied to each reconstructed LCU in the picture and thefinal filtered reference picture data is provided to the storagecomponent 418. In some embodiments, the ALF component 434 is notpresent.

FIG. 5 is a block diagram of an example video decoder. The video decoderoperates to reverse the encoding operations, i.e., entropy coding,quantization, transformation, and prediction, performed by the videoencoder of FIG. 4 to regenerate the pictures of the original videosequence. In view of the above description of a video encoder, one ofordinary skill in the art will understand the functionality ofcomponents of the video decoder without detailed explanation.

The entropy decoding component 500 receives an entropy encoded(compressed) video bit stream and reverses the entropy encoding usingCABAC decoding to recover the encoded syntax elements, e.g., CU, PU, andTU structures of LCUs, quantized transform coefficients for CUs, motionvectors, prediction modes, significance maps and group significance mapsfor TUs, SAO parameters, etc. The decoded syntax elements are passed tothe various components of the decoder as needed. For example, decodedprediction modes are provided to the intra-prediction component (IP) 514or motion compensation component (MC) 510. If the decoded predictionmode is an inter-prediction mode, the entropy decoder 500 reconstructsthe motion vector(s) as needed and provides the motion vector(s) to themotion compensation component 510.

The inverse quantize component (IQ) 502 de-quantizes the quantizedtransform coefficients of the CUs. The inverse transform component(IDCT) 504 transforms the frequency domain data from the inversequantize component 502 back to the residual CUs. That is, the inversetransform component 504 applies an inverse unit transform, i.e., theinverse of the unit transform used for encoding, to the de-quantizedresidual coefficients to produce reconstructed residual values of theCUs. The inverse transform component 504 may perform a method for IDCTpruning using information from group significance maps as describedherein to produce reconstructed residual values.

A residual CU supplies one input of the addition component 506. Theother input of the addition component 506 comes from the mode switch508. When an inter-prediction mode is signaled in the encoded videostream, the mode switch 508 selects predicted PUs from the motioncompensation component 510 and when an intra-prediction mode issignaled, the mode switch selects predicted PUs from theintra-prediction component 514.

The motion compensation component (MC) 510 receives reference data fromthe storage component 512 and applies the motion compensation computedby the encoder and transmitted in the encoded video bit stream to thereference data to generate a predicted PU. That is, the motioncompensation component 510 uses the motion vector(s) from the entropydecoder 500 and the reference data to generate a predicted PU.

The intra-prediction component (IP) 514 receives reconstructed samplesfrom previously reconstructed PUs of a current picture from the storagecomponent 512 and performs the intra-prediction computed by the encoderas signaled by an intra-prediction mode transmitted in the encoded videobit stream using the reconstructed samples as needed to generate apredicted PU.

The addition component 506 generates a reconstructed CU by adding thepredicted PUs selected by the mode switch 508 and the residual CU. Theoutput of the addition component 506, i.e., the reconstructed CUs, isstored in the storage component 512 for use by the intra-predictioncomponent 514.

In-loop filters may be applied to reconstructed picture data to improvethe quality of the decoded pictures and the quality of the referencepicture data used for decoding of subsequent pictures. The appliedin-loop filters are the same as those of the encoder, i.e., a deblockingfilter 516, a sample adaptive offset filter (SAO) 518, and an adaptiveloop filter (ALF) 520. The in-loop filters may be applied on anLCU-by-LCU basis and the final filtered reference picture data isprovided to the storage component 512. In some embodiments, the ALFcomponent 520 is not present.

FIGS. 6 and 8 are flow diagrams of methods for IDCT pruning usinginformation from a group significance map corresponding to a TU(transform block). Embodiments may be performed as part of IDCTcomputation in both a decoder and an encoder. If the methods areperformed in a decoder, the group significance map corresponding to thetransform block is first decoded from the compressed bit stream. Forsimplicity of explanation, embodiments are described assuming row-columnorder for application of the 1D IDCTs, i.e., that a 1D IDCT is firstapplied in the horizontal direction to the transform block, and then a1D IDCT is applied in the vertical direction to the interim resultsblock. One of ordinary skill in the art will understand otherembodiments in which column-row order is used for application of the 1DIDCTs, i.e., that a 1D IDCT is first applied in the vertical directionto the transform block, and then a 1D IDCT is applied in the horizontaldirection to the interim results block, without need for additionalexplanation.

Referring first to the method of FIG. 6, initially an upper bound on thenumber of rows of the transform block that may include significant(non-zero) coefficients is determined 602 from the group significancemap. Assuming that the group significance map has N rows and M columns,the number of rows that may include significant coefficients may bedetermined, for example, by starting with the significant coefficientgroup flag at position (N,M) (the bottom right position) of the map andscanning backward in reverse raster scan order until a flag with a valueof 1 is found. Note that this first non-zero significant coefficientgroup flag corresponds to a 4×4 block of the transform block containingthe last non-zero coefficient value in the transform block. Assumingthat the first row of the group significance map is row 0 andcoordinates of the first non-zero flag are (x,y), the upper bound on thenumber of rows of the transform block that may include significantcoefficients may be computed as 4(x+1).

A 1D IDCT is then computed 604 on the first 4(x+1) rows of the transformblock to generate the first 4(x+1) rows of the interim results block.The remaining rows in the interim results block are assumed to be 0.Subsequently, a 1D IDCT is computed 606 on all columns of the interimresults block to generate the residual block, and the residual block isoutput 608 for further processing.

FIG. 7 shows an example of the IDCT pruning of the method of FIG. 6. Thenon-shaded regions of each block indicate the region of the blockcontaining only zero coefficients. In this example, the input transformblock 700 is the 16×16 transform block 100 of FIG. 1. The significancemap and the group significance map for this transform block are shown inFIGS. 2A and 2B. The only significant coefficient group flag with avalue of 1 in the group significance map is at position (0,0) in themap. Thus, the number of rows on which the initial 1D IDCT is to becomputed is 4(0+1)=4. The first four rows of the transform block 700 aretransformed using the 1D IDCT to generate the first four rows of theinterim results block 702 as only the first 4 rows of transform block700 may have non-zero values. Then, all of the columns of the interimresults block 702 are transformed using the 1D IDCT to generate thefinal inversely transformed output block 704, i.e., the residual block.

Referring now to the method of FIG. 8, the method provides optimizedIDCT pruning for predetermined categories of rectangular distributionpatterns of non-zero coefficients in transform blocks. As is explainedin more detail below, the rectangular distribution pattern of non-zerocoefficients in a transform block can be determined from information inthe corresponding group significance map. The particular categories ofrectangular distribution patterns with optimized IDCT pruningimplementations provided in embodiments are a design decision. FIG. 9shows some example distribution categories for a 16×16 transform blockand FIG. 10 shows some example distribution categories for a 32×32transform block. These example distribution categories are assumedduring the description of the method. However, one of ordinary skill inthe art will understand that embodiments are not limited to theseparticular distribution categories.

Referring again to FIG. 8, initially, the rectangular distributionpattern of non-zero coefficients in the transform block is determined802 from the group significance map, and a determination 804 is made asto whether or not the distribution pattern fits in one of thepredetermined distribution categories. The rectangular distribution ofnon-zero coefficients in a transform block is bounded by the rightmostcolumn of the group significance map containing a non-zero significantcoefficient group flag and the bottom-most row of the map containing anon-zero flag. The column number of the rightmost column and the rownumber of the bottom-most row of the distribution pattern are used todetermine if the distribution pattern of the transform block fits intoone of the predetermined distribution categories.

Assuming that the group significance map has N rows and M columns, thecolumn number of the rightmost column and the row number of thebottom-most row may be found as follows. Beginning with column M andmoving in descending column order, the flag values in each column of thegroup significance map are checked for a non-zero flag value. The firstcolumn found with a non-zero flag value indicates the rightmost boundaryof the distribution pattern. This column may be referred to as column A.Beginning with row N and moving in descending row order, the flag valuesin each row of the group significance map are checked for a non-zeroflag value. The first row with a non-zero flag value indicates thebottom-most boundary of the distribution pattern. This row may bereferred to as row B.

The row number B and column number A may then be used to determinewhether or not the distribution pattern fits within one of thepredetermined distribution categories. For the example distributioncategories of FIG. 9, the column and row numbers of a group significancemap corresponding to the L4 category are A=B=1, the column and rownumbers corresponding to the L8 category are A=B=2, the column and rownumbers corresponding to the V8 category are A=4 and B=2, and column androw numbers corresponding to the H8 category are A=2 and B=4. For theexample distribution categories of FIG. 10, the column and row numbersof a group significance map corresponding to the L4 category are A=B=1,the column and row numbers corresponding to the L8 category are A=B=2,the column and row numbers corresponding to the L16 category are A=B=4,the column and row numbers corresponding to the V16 category are A=8 andB=4, and column and row numbers corresponding to the H16 category areA=4 and B=8.

For example, consider the following group significance map for a 16×16transform block:

1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0.For this example, A=2 and B=2. Thus, the distribution pattern of thetransform block fits in the L8 category of FIG. 9. In another example,consider the following group significance map for a 16×16 transform:

1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0.For this example, A=2 and B=4. Thus, the distribution pattern of thetransform block fits in the H8 category of FIG. 9.

Referring again to FIG. 8, if the distribution pattern of the transformblock fits in one of the distribution categories 804, then an optimizedIDCT with pruning specific to the particular distribution category isperformed 806 on the transform block to generate the residual block andthe residual block is output 808 for further processing. As can be seenfrom the example distribution categories of FIGS. 9 and 10, for a givendistribution category, it is known that certain rows and/or columns of atransform block with the corresponding distribution pattern contain onlyzero-value coefficients. This a priori knowledge may be used to providean optimized 1D IDCT with pruning tailored for the particularcombination of all zero rows and/or columns of a distribution category.

For example, the unpruned 1D 16-pt IDCT for a 16×16 transform blockwould be computed as per the formula of FIG. 11 where X0-X15 are theinputs and the Ci are IDCT coefficients. If the distribution category isL4 of FIG. 9, then it is known that for any transform block having thisdistribution pattern, all coefficient values in the transform blockexcept those in the 4×4 block are zero. Thus, the multiplications of the1D IDCT for any coefficient values outside of this block may be pruned.An optimized implementation for this L4 distribution category as per theformula of FIG. 12 may be used in which the transform coefficient matrixincludes only the first four columns of the original 16×16 transformmatrix and the input vector includes only the first four coefficientvalues in a row of the transform block. This optimized implementationfor the L4 distribution category may be denoted as an L4 1D IDCT. Asimilar optimized implementation for the L8 distribution category may bedenoted as an L8 1D IDCT, etc. One of ordinary skill in the art willunderstand similar optimized implementations for the other exampledistribution categories of FIGS. 9 and 10. Note that for distributioncategories such as L4 and L8 of FIG. 9 and L4, L8, and L16 of FIG. 10,the optimized Lx 1D IDCT may be used for both the rows of the transformblock and the columns of the interim results block.

Other optimized 1D IDCT implementations may also be used, such as anoptimized implementation built on even-odd decomposition of the relevantportion of the transform matrix and the non-zero portion of the inputvector. For example, the unpruned 1D 16-pt IDCT for a 16×16 transformblock using even-odd decomposition would be computed as per the formulasof FIG. 13. A optimized implementation for the L4 distribution categoryas per the formulas of FIG. 14 may be used in which the even and oddtransform coefficient matrices include only the even and odd columns ofthe first four columns of the original 16×16 transform matrix and theeven and odd input vectors include only the even and odd inputs from thefirst four coefficient values in a row of the transform block. FIG. 13shows an even-odd decomposition for distribution category L4 of FIG. 9.This optimized implementation for the L4 distribution category may bedenoted as an L4 1D IDCT. A similar optimized implementation for the L8distribution category may be denoted as an L8 1D IDCT, etc. One ofordinary skill in the art will understand similar optimizedimplementations for the other example distribution categories of FIGS. 9and 10.

Referring again to FIG. 8, if the distribution pattern of the transformblock does not fit in one of the distribution categories 804, then thetransform block is inverse transformed with an alternative pruningtechnique. First, an upper bound on the number of rows of the transformblock that may include significant (non-zero) coefficients is determined810 from the group significance map. Assuming that the groupsignificance map has N rows and M columns, the number of rows that mayinclude at least one significant coefficient may be determined, forexample, by starting with the significant coefficient group flag atposition (N,M) (the bottom right position) of the map and scanningbackward in reverse raster scan order until a flag with a value of 1 isfound. Note that this first non-zero significant coefficient group flagcorresponds to a 4×4 block of the transform block containing the lastnon-zero coefficient value in the transform block. Assuming that thefirst row of the group significance map is row 0 and coordinates of thefirst non-zero flag are (x,y), the upper bound on the number of rows ofthe transform block that may include significant coefficients may becomputed as 4(x+1).

A 1D IDCT is then computed 812 on the first 4(x+1) rows of the transformblock to generate the first 4(x+1) rows of the interim results block.The remaining rows in the interim results block are assumed to be 0.Subsequently, a 1D IDCT is computed 814 on all columns of the interimresults block to generate the residual block, and the residual block isoutput 808 for further processing.

FIG. 15 is a block diagram of an example digital system suitable for useas an embedded system that may be configured to perform IDCT pruning asdescribed herein during encoding of a video stream and/or duringdecoding of an encoded (compressed) video bit stream. This examplesystem-on-a-chip (SoC) is representative of one of a family of DaVinci™Digital Media Processors, available from Texas Instruments, Inc. ThisSoC is described in more detail in “TMS320DM6467 Digital MediaSystem-on-Chip”, SPRS403G, December 2007 or later, which is incorporatedby reference herein.

The SoC 1500 is a programmable platform designed to meet the processingneeds of applications such as video encode/decode/transcode/transrate,video surveillance, video conferencing, set-top box, medical imaging,media server, gaming, digital signage, etc. The SoC 1500 providessupport for multiple operating systems, multiple user interfaces, andhigh processing performance through the flexibility of a fullyintegrated mixed processor solution. The device combines multipleprocessing cores with shared memory for programmable video and audioprocessing with a highly-integrated peripheral set on common integratedsubstrate.

The dual-core architecture of the SoC 1500 provides benefits of both DSPand Reduced Instruction Set Computer (RISC) technologies, incorporatinga DSP core and an ARM926EJ-S core. The ARM926EJ-S is a 32-bit RISCprocessor core that performs 32-bit or 16-bit instructions and processes32-bit, 16-bit, or 8-bit data. The DSP core is a TMS320C64x+™ core witha very-long-instruction-word (VLIW) architecture. In general, the ARM isresponsible for configuration and control of the SoC 1500, including theDSP Subsystem, the video data conversion engine (VDCE), and a majorityof the peripherals and external memories. The switched central resource(SCR) is an interconnect system that provides low-latency connectivitybetween master peripherals and slave peripherals. The SCR is thedecoding, routing, and arbitration logic that enables the connectionbetween multiple masters and slaves that are connected to it.

The SoC 1500 also includes application-specific hardware logic, on-chipmemory, and additional on-chip peripherals. The peripheral set includes:a configurable video port (Video Port I/F), an Ethernet MAC (EMAC) witha Management Data Input/Output (MDIO) module, a 4-bit transfer/4-bitreceive VLYNQ interface, an inter-integrated circuit (I2C) businterface, multichannel audio serial ports (McASP), general-purposetimers, a watchdog timer, a configurable host port interface (HPI);general-purpose input/output (GPIO) with programmable interrupt/eventgeneration modes, multiplexed with other peripherals, UART interfaceswith modem interface signals, pulse width modulators (PWM), an ATAinterface, a peripheral component interface (PCI), and external memoryinterfaces (EMIFA, DDR2). The video port UF is a receiver andtransmitter of video data with two input channels and two outputchannels that may be configured for standard definition television(SDTV) video data, high definition television (HDTV) video data, and rawvideo data capture.

As shown in FIG. 15, the SoC 1500 includes two high-definitionvideo/imaging coprocessors (HDVICP) and a video data conversion engine(VDCE) to offload many video and image processing tasks from the DSPcore. The VDCE supports video frame resizing, anti-aliasing, chrominancesignal format conversion, edge padding, color blending, etc. The HDVICPcoprocessors are designed to perform computational operations requiredfor video encoding such as motion estimation, motion compensation,intra-prediction, transformation, and quantization. Further, thedistinct circuitry in the HDVICP coprocessors that may be used forspecific computation operations is designed to operate in a pipelinefashion under the control of the ARM subsystem and/or the DSP subsystem.

As was previously mentioned, the SoC 1500 may be configured to performIDCT pruning as described herein during encoding of a video streamand/or during decoding of an encoded (compressed) video bit stream. Forexample, the coding control of the video encoder of FIG. 4 may beexecuted on the DSP subsystem or the ARM subsystem and at least some ofthe computational operations of the block processing, including theintra-prediction and inter-prediction of mode selection, transformation,quantization, entropy encoding, inverse quantization, and inversetransformation (IDCT) may be executed on the HDVICP coprocessors.Similarly, at least some of the computational operations of the variouscomponents of the video decoder of FIG. 5, including entropy decoding,inverse quantization, inverse transformation (IDCT), intra-prediction,and motion compensation may be executed on the HDVICP coprocessors.

Other Embodiments

While the invention has been described with respect to a limited numberof embodiments, those skilled in the art, having benefit of thisdisclosure, will appreciate that other embodiments can be devised whichdo not depart from the scope of the invention as disclosed herein.

For example, embodiments and examples have been described hereinassuming a square transform block. Transform blocks may also berectangular, e.g., 8×16, 16×8, 16×32, 32×16, etc. One of ordinary skillin the art will understand embodiments that include rectangulartransform blocks without need of further description.

In another example, embodiments have been described herein assuming thata significant coefficient group flag in a group significance mapcorresponds to a 4×4 sub-block of a significant coefficient map, andthus to a 4×4 sub-block of a transform block. One of ordinary skill inthe art will understand embodiments in which other sub-block sizes areused.

Embodiments of the methods, encoders, and decoders described herein maybe implemented in hardware, software, firmware, or any combinationthereof. If completely or partially implemented in software, thesoftware may be executed in one or more processors, such as amicroprocessor, application specific integrated circuit (ASIC), fieldprogrammable gate array (FPGA), or digital signal processor (DSP). Thesoftware instructions may be initially stored in a computer-readablemedium and loaded and executed in the processor. In some cases, thesoftware instructions may also be sold in a computer program product,which includes the computer-readable medium and packaging materials forthe computer-readable medium. In some cases, the software instructionsmay be distributed via removable computer readable media, via atransmission path from computer readable media on another digitalsystem, etc. Examples of computer-readable media include non-writablestorage media such as read-only memory devices, writable storage mediasuch as disks, flash memory, memory, or a combination thereof.

It is therefore contemplated that the appended claims will cover anysuch modifications of the embodiments as fall within the true scope ofthe invention.

What is claimed is:
 1. A method comprising: receiving, by a decoder, abit stream including: a transform block including transformcoefficients; and a group significance map including one or moresignificant coefficient group flags associated with the transform block;determining, by the decoder, a region of the transform block based onthe one or more significant coefficient group flags; and determining, bythe decoder, an output block based on an inverse discrete cosinetransformation (IDCT) of the region of the transform block.
 2. Themethod of claim 1, wherein: the bit stream includes a significance map;and the one or more significant coefficient group flags are indicativeof whether a respective one of a plurality of blocks in the significancemap includes at least one non-zero transform coefficient.
 3. The methodof claim 1, further comprising: determining, by the decoder, adistribution pattern of non-zero coefficients in the transform blockbased on the group significance map.
 4. The method of claim 3, wherein:the distribution pattern is rectangular.
 5. The method of claim 3,wherein: the group significance map includes N rows and M columns. 6.The method of claim 5, wherein: the determining of the distributionpattern includes: beginning with column M of the group significance mapand moving in descending column order until a first column of the groupsignificance map is detected in which the one or more significantcoefficient group flags has a first non-zero value; beginning with row Nof the group significance map and moving in descending row order until afirst row of the group significance map is detected in which the one ormore significant coefficient group flags has a second non-zero value;determining a boundary based on the first column of the groupsignificance map and the first row of the group significance map; andselecting the distribution pattern from a plurality of predetermineddistribution patterns based on the boundary.
 7. The method of claim 5,wherein: the determining of the distribution pattern includesdetermining an upper bound on a number of rows of the transform blockbased on the group significance map.
 8. The method of claim 7, wherein:the determining of the upper bound includes scanning the groupsignificance map in reverse raster scan order starting at a position(N,M) to detect a location of a third non-zero value; and the number ofrows of the transform block for the IDCT is based on the location of thethird non-zero value.
 9. The method of claim 8, further comprising:generating an interim block based on the IDCT of the number of rows; anddetermining the output block based on the IDCT of all columns of theinterim block.
 10. The method of claim 9, wherein: the location of thethird non-zero value is at a second position (x,y).
 11. An decodercomprising: an input configured to receive a bit stream, wherein the bitstream includes: a transform block including transform coefficients; anda group significance map including one or more significant coefficientgroup flags associated with the transform block; an inverse transformcomponent configured to: determine a region of the transform block basedon the one or more significant coefficient group flags; and determine anoutput block based on an inverse discrete cosine transformation (IDCT)of the region of the transform block.
 12. The decoder of claim 11,wherein: the bit stream includes a significance map; and the one or moresignificant coefficient group flags are indicative of whether arespective one of a plurality of blocks in the significance map includesat least one non-zero transform coefficient.
 13. The decoder of claim11, wherein the inverse transform component is further configured to:determine a distribution pattern of non-zero coefficients in thetransform block based on the group significance map.
 14. The decoder ofclaim 13, wherein: the distribution pattern is rectangular.
 15. Thedecoder of claim 13, wherein: the group significance map includes N rowsand M columns.
 16. The decoder of claim 15, wherein to determine thedistribution pattern of non-zero coefficients, the inverse transformcomponent is further configured to: detect a first column of the groupsignificance map in which the one or more significant coefficient groupflags has a first non-zero value, by beginning with column M of thegroup significance map and moving in descending column order until thefirst non-zero value is detected; detect a first row of the groupsignificance map in which the one or more significant coefficient groupflags has a second non-zero value, by beginning with row N of the groupsignificance map and moving in descending row order until the secondnon-zero value is detected; determine a boundary based on the firstcolumn of the group significance map and the first row of the groupsignificance map; and select the distribution pattern from a pluralityof predetermined distribution patterns based on the boundary.
 17. Thedecoder of claim 15, wherein to determine the distribution pattern ofnon-zero coefficients, the inverse transform component is furtherconfigured to: determine an upper bound on a number of rows of thetransform block based on the group significance map.
 18. The decoder ofclaim 17, wherein: to determine the upper bound, the inverse transformcomponent is configured to scan the group significance map in reverseraster scan order starting at a position (N,M) to detect a location of athird non-zero value; wherein the number of rows of the transform blockfor the IDCT is based on the location of the third non-zero value. 19.The decoder of claim 18, wherein the inverse transform component isfurther configured to: generate an interim block based on the IDCT ofthe number of rows; and determine the output block based on the IDCT ofall columns of the interim block.
 20. The decoder of claim 19, wherein:the location of the third non-zero value is at a second position (x,y).